Today, systems frequently use digital protocols and interfaces for data transmission between components, devices or elements. Such protocols or interfaces typically have a limited bandwidth regarding their transmission. For example, the bandwidth for a protocol or of an interface may be limited due to power considerations, cost considerations, electromagnetic compatibility considerations or other factors.
An example for such a system may be a sensor or other transmitter coupled to a control unit or other receiver. The sensor for example measures a physical signal, converts it to a digital value with a certain sampling rate and transmits it to a control unit using a transfer rate given by an interface and/or protocol used for the transmission.
The speed of such a system is in many cases limited by the interface used to transmit data via a communication channel. Assuming a certain transfer rate via the communication channel, a maximum bandwidth of the system according to the Nyquist-Shannon theorem may be at most half the transfer rate to avoid so-called aliasing effects. When aliasing effects occur, higher frequencies are “folded back” to the frequency band transmitted.
In less critical cases, such aliasing may just reduce signal quality (constituting essentially additional noise), but in other cases it may alter the signals such that errors in transmitted data or other faults may occur. For example, in cases where a data signal to be transmitted(e.g. a physical entity measured by a sensor device with digital transmitter) cannot be assumed to be band limited, such higher frequency components (above half the transmission frequency) may cause a wrong readout of sensor data.
Conventionally, so-called anti-aliasing filters (which may be essentially low-pass filters) are used to reduce or eliminate aliasing. Essentially, with such filters signal components above the “allowed” frequency band are filtered out or at least attenuated.
In some applications, it is required that a system has a low step response and thus requires a low latency time regarding the transmission of data to the control unit. In other words, a fast settling time of a signal to a final value may be required. However, an anti-aliasing filter may increase such a settling time (e.g. corresponding to an RC value of the filter), which may correspond to an increased latency as well.
To give an example, for example in a system a settling time of 100 μs is required as a so-called 5 τ-value, which essentially indicates that about 99.9% of the final signal value has to be reached after 100 μs. If such a requirement is to be implemented in an interface with a 400 μs update rate, the “sampling frequency” of the transmission would correspond to 2.5 kHz. This, to avoid aliasing effects, would require an anti-aliasing filter with a corner frequency lower than 1.25 kHz.
This filter defines basically the fastest possible settling time. Current realistic filter implementations which can be realized with reasonable efforts and costs and providing a useful step response, however, would result in a 5 τ-value much larger than the required 100 μs, depending on the chosen filter type and complexity and furthermore depending on the attenuation at the corner frequency to effectively prevent anti-aliasing problems.
Especially in safety-critical or mission-critical systems, where such redundant data transmission principles may be used, further margins may be desired to ensure a proper function and error tolerance of such a classic setup on the one hand, which will cause an even more reduced bandwidth and higher latency in the transmitted data on the other hand.